AIMC Topic: Cornea

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Artificial Intelligence Aided Analysis of Anterior Segment Optical Coherence Tomography Imaging to Monitor the Device-Cornea Joint After Synthetic Cornea Implantation.

Translational vision science & technology
PURPOSE: The purpose of this study was to assess the utility of artificial intelligence (AI) assisted analysis of anterior segment optical coherence tomography (AS-OCT) imaging of the device-cornea joint in predicting outcomes of an intrastromal synt...

Reconstruction of highly and extremely aberrated wavefront for ocular Shack-Hartmann sensor using multi-task Attention-UNet.

Experimental eye research
In certain ocular conditions, such as in eyes with keratoconus or after corneal laser surgery, Higher Order Aberrations (HOAs) may be dramatically elevated. Accurately recording interpretable wavefronts in such highly aberrated eyes using Shack-Hartm...

MCOA: A Comprehensive Multimodal Dataset for Advancing Deep Learning in Corneal Opacity Assessment.

Scientific data
Corneal opacity remains a major global cause of vision impairment. Its severity is typically assessed subjectively by clinicians using slit lamp examinations of the anterior segment. While anterior segment optical coherence tomography (AS-OCT) provid...

Using Artificial Intelligence for an Efficient Prediction of Outcomes of Deep Anterior Lamellar Keratoplasty (DALK) in Advanced Keratoconus.

Translational vision science & technology
PURPOSE: To identify and analyze clinical risk factors and imaging parameters influencing the outcomes of deep anterior lamellar keratoplasty (DALK) for advanced keratoconus (KC) using an artificial intelligence (AI) model.

AI for Corneal Imaging: How Will This Help Us Take Care of Our Patients?

Cornea
As artificial intelligence continues to evolve at a rapid pace, there is growing enthusiasm surrounding the potential for novel applications in corneal imaging. This article provides an overview of the potential for such applications, as well as the ...

[Application of neural networks for improving the methods of assessment of corneal nerve fibers (preliminary report)].

Vestnik oftalmologii
UNLABELLED: Processing large datasets using artificial intelligence is a promising approach in disease diagnosis and monitoring that focuses on improving research algorithms for existing technologies. Interest in studying corneal nerve fibers (CNFs) ...

Forme fruste keratoconus detection with OCT corneal topography using artificial intelligence algorithms.

Journal of cataract and refractive surgery
PURPOSE: To differentiate a normal cornea from a forme fruste keratoconus (FFKC) with the swept-source optical coherence tomography (SS-OCT) topography CASIA 2 using machine learning artificial intelligence algorithms.

Ocular Biometric Components in Hyperopic Children and a Machine Learning-Based Model to Predict Axial Length.

Translational vision science & technology
PURPOSE: The purpose of this study was to investigate the development of optical biometric components in children with hyperopia, and apply a machine-learning model to predict axial length.

Keratoconus Progression Determined at the First Visit: A Deep Learning Approach With Fusion of Imaging and Numerical Clinical Data.

Translational vision science & technology
PURPOSE: Multiple clinical visits are necessary to determine progression of keratoconus before offering corneal cross-linking. The purpose of this study was to develop a neural network that can potentially predict progression during the initial visit...

[Evaluation of the efficacy of antifibrotic drugs on cell cultures in Salzmann's nodular degeneration].

Vestnik oftalmologii
UNLABELLED: Excessive production of extracellular matrix is a key component in the pathogenesis of Salzmann's nodular degeneration (SND). studies of drugs that suppress excessive fibroblast activity may become crucial in developing pathogenetically ...